{"version":"1.0","type":"rich","title":"wine_load","description":"This example visualizes the Wine Recognition dataset, showing the first few rows of the feature matrix as a tabular preview. The code loads the dataset using `load_wine()` from scikit-learn, then constructs a pandas DataFrame with `data.data` and `data.feature_names` as columns. The rendering displays the resulting `wine.head()` table, which shows the first five samples with their numerical attributes such as alcohol content and malic acid. The visualization relies on pandas' default DataFrame display formatting to present the data in a structured grid, making the dataset’s structure and feature values immediately visible.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-b74e66dc364eb37693530ccb9dee1db2?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}